Senior Machine Learning Engineer

Posted 8 Days Ago
Be an Early Applicant
Barcelona, Cataluña, ESP
In-Office
55K-70K Annually
Senior level
Digital Media • Fintech • Information Technology
The Role
Owns the end-to-end lifecycle of machine learning and LLM solutions, including development, fine-tuning, evaluation, deployment, monitoring, retraining, inference optimization, and scalable MLOps pipelines. The role involves improving experimentation, versioning, A/B testing, and ML infrastructure; collaborating with data, engineering, and product teams; contributing to architecture; and mentoring junior ML engineers.
Summary Generated by Built In

Job Description:


Senior Machine Learning Engineer
Dow Jones Barcelona-Spain
About the Team:

Our Technology team drives the evolution of our Technology, Engineering, Data,
Product and User Experience functions. With a keen focus on delivering cutting-edge
solutions, we shape the digital landscape for our customers, readers and users. From
revolutionizing visuals to optimizing tools and harnessing the power of data, mobile,
video and social platforms, our team is committed to providing a seamless and
immersive experience across all touchpoints. Collaborating closely with our newsrooms
and strategic partners, we spearhead the development of groundbreaking products and
technologies.

About the Role:

We are seeking a highly experienced and technically adept Senior Machine Learning
Engineer to join our team. In this pivotal role, you will own the entire lifecycle of MLOps
from optimization to deployment, with a strong focus on LLMOps. This position
demands a strong blend of hands-on technical expertise, strategic thinking, and the
ability to foster innovation within a dynamic environment.

You Will:
  • Develop and manage LLM-based solutions, including semantic layer
    development, fine-tuning, model evaluation, deployment strategies, and the
    development of agent and multi-agent systems.

  • Own end-to-end ML model development, optimization, and deployment.

  • Ensure the scalability, efficiency, and reliability of ML pipelines.

  • Design and implement robust model monitoring and retraining strategies.

  • Optimize model inference and performance for production environments.

  • Collaborate closely with data scientists, engineers, and product teams to
    integrate ML solutions.

  • Improve experimentation frameworks, model versioning, and A/B testing
    strategies.

  • Ensure best practices in MLOps, including automation, reproducibility, and CI/CD
    for ML.

  • Contribute to architectural decisions and improve ML infrastructure.

  • Mentor and provide technical guidance to junior ML engineers.


You Have:
  • A Bachelor's degree in Computer Science, Statistics, Mathematics, or a related
    quantitative field; a Master's degree or Ph.D. is a strong plus.

  • 2-4 years of professional experience in machine learning with a strong portfolio
    of models deployed in a production environment.

  • Strong experience with LLMOps, including fine-tuning frameworks, prompt
    engineering, and managing the lifecycle of large language models, as well as
    experience in the development of agent and multi-agent systems.

  • Advanced hands-on experience with cloud-based data warehouse solutions;
    Snowflake experience strongly preferred.

  • Proficiency in Python and SQL and deep, hands-on experience with ML
    frameworks like TensorFlow, PyTorch.

  • A grasp of the broader data science toolkit, including libraries like Scikit-learn,
    Pandas, and NumPy.

  • Experience building and maintaining MLOps pipelines using tools like MLflow, or
    Airflow.

  • Experience with cloud platforms (AWS, GCP, or Azure) and large-scale data
    processing frameworks like Spark or Dask is preferred.

Our Benefits
  • Comprehensive Healthcare Plans for you and your family (paid by Dow Jones)

  • Extra paid Time Off (30 days of holidays/year)

  • Possibility to work remotely for 3 months/year (desplazamiento program) and one week of remote work per quarter

  • Meal benefit with Pluxee (171€/month on top of your salary)

  • Retirement Plans (Dow Jones will pay 2% of a members Pensionable Salary and match employee contribution up to a maximum of 3 %).

  • Live insurance

  • Well-being Resources (185€ allowance per quarter, Classpass, Spring Health, etc.)

  • Family Care Benefits & Caregiving Support

  • Hone and Linkedin learning courses for your further development

  • Employee Referral Program

Learn more about us and our benefits click here


Equal Opportunity Employer


All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, national origin, protected veteran status, disability status or any other protected characteristic. We strongly encourage applications from all qualified individuals, including women, people with disabilities, and those from underrepresented groups.

Reasonable Accommodation


We are committed to providing reasonable accommodation for qualified individuals with disabilities in our job application and/or interview process. If you need assistance or accommodation in completing your application or participating in an interview due to a disability, email us at [email protected]. Please put "Reasonable Accommodation" in the subject line and provide a brief description of the type of assistance you need. This inbox will not be monitored for application status updates.

Please refer to the privacy notice at the bottom of this page for submitting any data access, deletion, or other data subject rights requests, where permitted under your local laws and regulations.


Business Area:


Dow Jones - Technology

Job Category:


Software Product Engineering

Union Status:


Non-Union / A clear and likely internal candidate
Base Pay Range: 55,000 € - 70,000 €

We’re committed to offering competitive and flexible compensation to attract top talent. This pay range reflects our good faith estimate for the role and may vary based on a candidate’s experience, skills, location, and other relevant factors.


For bonus-eligible roles, targets are determined based on multiple considerations, including market benchmarks and individual contributions.


For benefits-eligible roles, we offer a comprehensive and competitive benefits package covering health, retirement, wellbeing, and more, along with optional benefits to meet the diverse needs of our employees.


Skills Required

  • Bachelor's degree in Computer Science, Statistics, Mathematics, or a related quantitative field
  • 2-4 years of professional machine learning experience
  • Strong portfolio of machine learning models deployed in production
  • Experience with LLMOps, including fine-tuning frameworks, prompt engineering, and large language model lifecycle management
  • Experience developing agent and multi-agent systems
  • Advanced hands-on experience with cloud-based data warehouse solutions
  • Snowflake experience
  • Proficiency in Python and SQL
  • Hands-on experience with TensorFlow and PyTorch
  • Familiarity with Scikit-learn, Pandas, and NumPy
  • Experience building and maintaining MLOps pipelines using MLflow or Airflow
  • Experience with AWS, GCP, or Azure
  • Experience with Spark or Dask for large-scale data processing
  • Master's degree or Ph.D.
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The Company
HQ: New York, NY
4,898 Employees
Year Founded: 1882

What We Do

When you join Dow Jones, you become part of the most dynamic, creative and savvy news and information companies in the world. As a global leader in news and business intelligence, we're newswires, websites, newspapers, apps, newsletters, databases, magazines, and video --including some of the widest-read and most-respected brands, like The Wall Street Journal, Factiva, Barron’s, MarketWatch, Financial News, DJX, Dow Jones Risk & Compliance, Dow Jones Newswires, and Dow Jones VentureSource. Our products inform the discussions and decisions that are vital to the world's commerce, while our databases make the business world more transparent. We continually develop technology to transform information into insight and prosperity. We enlighten and inspire audiences around the globe with authoritative, differentiated and trusted content.

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